pandas 如何将列中的值更改为二进制？
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How to change values in a column into binary?
提问by Akshat Bhardwaj
New to python and I am stuck at this. My CSV file contain this:
python的新手，我被困在这个问题上。我的 CSV 文件包含以下内容：
Sr,Gender
1,Male
2,Male
3,Female
Now I want to convert the Gender values into binary so the the file will look something like:
现在我想将 Gender 值转换为二进制文件，这样文件看起来像：
Sr,Gender
1,1
2,1
3,0
So, I imported the CSV file as dataand ran this code:
因此，我将 CSV 文件导入为data并运行以下代码：
data["Gender_new"]=1
data["Gender_new"][data["Gender"]=="Male"]=0
data["Gender_new"]=1=data["Gender_new"].astype(float)
But I got the error ValueError: could not convert string 'Male' to float:
但我得到了错误 ValueError: could not convert string 'Male' to float:
What am I doing wrong and how can I make this work?
我做错了什么，我怎样才能做到这一点？
Thanks
谢谢
回答by Nidhin Sajeev
Try this:
尝试这个：
import pandas as pd
file = open("your.csv", "r")
data = pd.read_csv(file, sep = ",")
gender = {'male': 1,'female': 0}
data.Gender = [gender[item] for item in data.Gender]
print(data)
Or
或者
data.Gender[data.Gender == 'male'] = 1
data.Gender[data.Gender == 'female'] = 0
print(data)
回答by Burhan Khalid
You can do the conversion as you load the file:
您可以在加载文件时进行转换：
d = pandas.read_csv('yourfile.csv', converters={'Gender': lambda x: int(x == 'Male')})
The convertersargument takes a dictionary whose keys are the column names (or indices), and the value is a function to call for each item. The function must return the converted value.
该converters参数使用字典的键是列名（或指数），该值是要求每个项目的功能。该函数必须返回转换后的值。
The other way to do it is to convert it once you have the dataframe, as @DJK pointed in their comment:
另一种方法是在拥有数据帧后转换它，正如@DJK 在他们的评论中指出的那样：
data['Gender'] = (data['Gender'] == 'Male').astype(int)
